Analysis and Correlation between a Non-Invasive Sensor Network System in the Room and the Improvement of Sleep Quality
, Carolina Del-Valle-Soto 1,*,†, Paolo Visconti 2 and Fabiola Cortes-Chavez 1
Round 1
Reviewer 1 Report
In this manuscript authors addressed the problem of using non-invasive technologies that can help improve the quality of people’s sleep at a low cost. The paper reviews the sleep quality of a group of people by analyzing their good and bad sleeping habits, and derive algorithm based on information gahered by non-invasive sensor network in the person’s room for monitoring factors that help them fall asleep. The algorithm analyze vital signs and health conditions in order to relate these parameters to the person’s way of sleeping. The experimetn resulted with about a 15% improvement in sleep quality when the designed system is used. The authors compared the implementations given by the network with wearables to show the improvement in the behavior of the person’s sleep. Also, a short comparison to similar work is presented.
The authors are suggested to give more elaborate description (in 1.1. Related work section) of prior work in the are used for comparison in section 2.9. Comparison with other works. Also, some discussion should be given in section 2.9 - not just the tabel as is now.
Author Response
Dear
Editor
Future Internet
We are submitting the paper:
“Analysis and correlation between a non-invasive sensor network system in the room and the improvement of sleep quality”
Authored by: Eduardo Morales-Vizcarra, Carolina Del-Valle-Soto*, Paolo Visconti, and Fabiola Cortes-Chavez.
We would like to thank the reviewers and editors for their detailed analysis of the manuscript; the comments are very valuable to us. In the revised version of the paper, we have incorporated the all changes recommended by the reviewers.
Comments to all observations and suggestions including point-by-point responses are addressed in the following text.
Reviewer 1 comments
Comment 1: In this manuscript authors addressed the problem of using non-invasive technologies that can help improve the quality of people’s sleep at a low cost. The paper reviews the sleep quality of a group of people by analyzing their good and bad sleeping habits, and derive algorithm based on information gahered by non-invasive sensor network in the person’s room for monitoring factors that help them fall asleep. The algorithm analyze vital signs and health conditions in order to relate these parameters to the person’s way of sleeping. The experimetn resulted with about a 15% improvement in sleep quality when the designed system is used. The authors compared the implementations given by the network with wearables to show the improvement in the behavior of the person’s sleep. Also, a short comparison to similar work is presented.
The authors are suggested to give more elaborate description (in 1.1. Related work section) of prior work in the are used for comparison in section 2.9. Comparison with other works. Also, some discussion should be given in section 2.9 - not just the tabel as is now.
Response: We thank to the Reviewer for his/her valuable and deep comment that will improve our work remarkably. The Reviewer is right, and we have substantially improved the Related Work Section.
We have placed subsection 2.9 "Comparison with other work," following the subsection "Related Work" to give the paper more organization. We have complemented the work related to current technologies for home sleep monitoring. In addition, we have added a higher impact to the Comparison Table in this section.
We have increased the references with updated works that impact science and technology developments that describe sleep in human health.
Thank you very much.
Sincerely,
Carolina Del-Valle-Soto
Corresponding author
Universidad Panamericana. Facultad de Ingeniería. Álvaro del Portillo 49, Zapopan, Jalisco, 45010, México.
Phone: +52 (33) 13682200 | Ext. 4866
Email: [email protected]
Author Response File: 
Author Response.pdf
Reviewer 2 Report
This paper uses IOT technology to detect and improve people's sleep quality, which is very meaningful. My personal opinions on the revision of this article are as follows:
1. A large number of words are used to describe the experimental scenes and methods, but this is not intuitive. It is suggested to use the form of table to describe the important parameters of the experiment in detail, especially the number of experimental personnel. In the second section, the number of samples is introduced as n = 32. In the third section, it is said that there are 50 men and 50 women in each group. What is the inconsistency between these two data?
2. This paper focuses on monitoring and improving the sleep health of the tested personnel, and formulates a questionnaire. Generally speaking, sleep quality is closely related to personal sleep habits, but it is also inseparable from one's basic health. The article does not introduce whether the subjects have basic diseases or basic health conditions. Please supplement.
3. Examples of data sources and sleep improvement applications shown in FIGS. 14 and 16. It has no academic value. I suggest it be removed.
4. Figure 15 lists the improvement of sleep quality, but the sleep quality described in the article has many factors, and only the qualitative description is given in Section 2. How are the quantitative results calculated here? Please supplement the calculation model and basis.
Author Response
Dear
Editor
Future Internet
We are submitting the paper:
“Analysis and correlation between a non-invasive sensor network system in the room and the improvement of sleep quality”
Authored by: Eduardo Morales-Vizcarra, Carolina Del-Valle-Soto*, Paolo Visconti, and Fabiola Cortes-Chavez.
We would like to thank the reviewers and editors for their detailed analysis of the manuscript; the comments are very valuable to us. In the revised version of the paper, we have incorporated the all changes recommended by the reviewers.
Comments to all observations and suggestions including point-by-point responses are addressed in the following text.
Reviewer 2 comments
Comment 1: This paper uses IOT technology to detect and improve people's sleep quality, which is very meaningful. My personal opinions on the revision of this article are as follows:
- A large number of words are used to describe the experimental scenes and methods, but this is not intuitive. It is suggested to use the form of table to describe the important parameters of the experiment in detail, especially the number of experimental personnel. In the second section, the number of samples is introduced as n = 32. In the third section, it is said that there are 50 men and 50 women in each group. What is the inconsistency between these two data?
Response: Thank you very much for your comment and your valuable contributions. We analyzed the results presented in the experiment and we agree on the comments. The experimental scenes and methods were just explained with a large number of words. In consequence, we added a table to show the results with the most important variables. In this table we provided further information about the amount of people involved in the experiment by parameter. Furthermore, talking about the inconsistency between the two numbers of samples, firstly we completed an experiment obtaining 32 samples to know people’s habits and with this, have a base to start with. Then, these samples helped us to develop an algorithm to test and get 50 more samples. These extra samples were helpful when using the sensor network. We appreciate the comment on this because it’s important to clarify how these two values complement each other by getting a better understanding of the experiment.
Comment 2: This paper focuses on monitoring and improving the sleep health of the tested personnel, and formulates a questionnaire. Generally speaking, sleep quality is closely related to personal sleep habits, but it is also inseparable from one's basic health. The article does not introduce whether the subjects have basic diseases or basic health conditions. Please supplement.
Response: The Reviewer notes a very good point. We added a Table with the questionnaire that was applied to the users before performing the experiments to detect primary diseases or basic health conditions. We have chosen a sample of 50 healthy people, non-smokers who do not have heart or lung conditions to avoid bias in the experiment. People who have answered "yes" to any of the questions in Table 3 have been discarded from the sample.
“shows the results of the qualitative approach which describes the variables used for the research with 32 samples. These variables are time of sleep, exposure to light and sleep position. The answers for each of the variables were analyzed by comparing whether the participants slept complete cycles or not, whether they had exposure to light or not and whether they slept on a side position, on a back or stomach position. We present the numerical approach of these results to illustrate them. With these results obtained from the 32 samples, we will develop an algorithm to test later on this study.”
Comment 3: Examples of data sources and sleep improvement applications shown in FIGS. 14 and 16. It has no academic value. I suggest it be removed.
Response: The reviewer makes an excellent point. We have improved the scientific content by removing figure 14. Also, if the reviewer agreed, we would leave figure 16 as these images show relevant information from real sleep applications. These data are helpful for the study thanks to the accurate information taken from real sensors already sold in different devices and reported by our experimental subjects. By comparing these results with the results we obtained during the study, we can identify how the person's sleep data improves in the presence of the algorithm. This is as true to our results. Figure 16 has been translated into English for ease.
Comment 4: Figure 15 lists the improvement of sleep quality, but the sleep quality described in the article has many factors, and only the qualitative description is given in Section 2. How are the quantitative results calculated here? Please supplement the calculation model and basis.
Response: This Figure, now Figure 18, needs to be better explained, as the Reviewer mentions. Data presented here is taken from the 50 people in the sample who experience the absence and presence of the algorithm in the sensor network in their room. It is essential to mention that external conditions can influence the experiment, such as the person's mood that day, mood swings, momentary changes in the family environment, etc. However, these data were taken quantitatively during the two weeks of experimentation with electronic devices suitable for medical use in homes. So, in the first week, people do not sleep with the sensor network in their room (no sensors). In the second week, people sleep with the sensor network in operation and the proposed algorithm activated in the devices (sensors). This Figure corresponds to the metrics described in Table 4. Here the behavior of the data is shown in a comparative way and its distribution. We observe how the algorithm's operation is consistent with the person's relaxation, and this impacts their way of sleeping. The foremost vital signs show improvements when people sleep with the sensor network in their room (sensors). Measurements are taken with medical devices used at home to measure temperature, heart rate, breathing frequency, and oxygen saturation. We take a measurement every hour while the subject is asleep. These measurements were made during the week when the subjects do not have the sensor network and during the week when they sleep with the sensor network in their room.
Thank you very much.
Sincerely,
Carolina Del-Valle-Soto
Corresponding author
Universidad Panamericana. Facultad de Ingeniería. Álvaro del Portillo 49, Zapopan, Jalisco, 45010, México.
Phone: +52 (33) 13682200 | Ext. 4866
Email: [email protected]
Author Response File: Author Response.pdf
Reviewer 3 Report
1. The quality of the scientific content on the background of sleeping is very shallow.
2. The presentation of the methods used is not enough for a scientific article. There is an image of the devices used to create the wireless network and the configuration of the central unit is presented in unnecessary detail. However, there is no information about the type of sensors, their detection accuracy, etc. This fundamentally calls into questioning the usability of the entire measurement.
3. Among the questions "what position did you sleep in?" It was not established scientifically how relevant it is. Furthermore, one usually does not remember it, and it may happen in many different poses.
4. The inscriptions "before/after experiments" are limited and unexplained under the graphs (then where is the data from?).
5. The mobile phone screen photos, from which data should be read, are of poor quality and do not have English subtitles.
6. In Table 1, the System type says "Invasive". With a sleep study, it is not described what is invasive, and what is not, but it seems like an exaggeration.
7. The results include a 9% increase in sleep quality for men and 15% for women. This could easily be a result of measuring technique inaccuracy. Such details of the experiment are not disclosed.
8. It is hard to understand the results of the measurements in Table 2 with the sensor and without the sensor network. So how did the measurement go? In the meanwhile, the differences are so small that they can simply be measurement errors.
9. The scale and ranges of the adjacent figures in the data stability chapter are different and subject to misunderstanding.
Author Response
Dear
Editor
Future Internet
We are submitting the paper:
“Analysis and correlation between a non-invasive sensor network system in the room and the improvement of sleep quality”
Authored by: Eduardo Morales-Vizcarra, Carolina Del-Valle-Soto*, Paolo Visconti, and Fabiola Cortes-Chavez.
We would like to thank the reviewers and editors for their detailed analysis of the manuscript; the comments are very valuable to us. In the revised version of the paper, we have incorporated the all changes recommended by the reviewers.
Comments to all observations and suggestions including point-by-point responses are addressed in the following text.
Reviewer 1 comments
Comment 1: In this manuscript authors addressed the problem of using non-invasive technologies that can help improve the quality of people’s sleep at a low cost. The paper reviews the sleep quality of a group of people by analyzing their good and bad sleeping habits, and derive algorithm based on information gahered by non-invasive sensor network in the person’s room for monitoring factors that help them fall asleep. The algorithm analyze vital signs and health conditions in order to relate these parameters to the person’s way of sleeping. The experimetn resulted with about a 15% improvement in sleep quality when the designed system is used. The authors compared the implementations given by the network with wearables to show the improvement in the behavior of the person’s sleep. Also, a short comparison to similar work is presented.
The authors are suggested to give more elaborate description (in 1.1. Related work section) of prior work in the are used for comparison in section 2.9. Comparison with other works. Also, some discussion should be given in section 2.9 - not just the tabel as is now.
Response: We thank to the Reviewer for his/her valuable and deep comment that will improve our work remarkably. The Reviewer is right, and we have substantially improved the Related Work Section.
We have placed subsection 2.9 "Comparison with other work," following the subsection "Related Work" to give the paper more organization. We have complemented the work related to current technologies for home sleep monitoring. In addition, we have added a higher impact to the Comparison Table in this section.
We have increased the references with updated works that impact science and technology developments that describe sleep in human health.
Reviewer 2 comments
Comment 1: This paper uses IOT technology to detect and improve people's sleep quality, which is very meaningful. My personal opinions on the revision of this article are as follows:
- A large number of words are used to describe the experimental scenes and methods, but this is not intuitive. It is suggested to use the form of table to describe the important parameters of the experiment in detail, especially the number of experimental personnel. In the second section, the number of samples is introduced as n = 32. In the third section, it is said that there are 50 men and 50 women in each group. What is the inconsistency between these two data?
Response: Thank you very much for your comment and your valuable contributions. We analyzed the results presented in the experiment and we agree on the comments. The experimental scenes and methods were just explained with a large number of words. In consequence, we added a table to show the results with the most important variables. In this table we provided further information about the amount of people involved in the experiment by parameter. Furthermore, talking about the inconsistency between the two numbers of samples, firstly we completed an experiment obtaining 32 samples to know people’s habits and with this, have a base to start with. Then, these samples helped us to develop an algorithm to test and get 50 more samples. These extra samples were helpful when using the sensor network. We appreciate the comment on this because it’s important to clarify how these two values complement each other by getting a better understanding of the experiment.
Comment 2: This paper focuses on monitoring and improving the sleep health of the tested personnel, and formulates a questionnaire. Generally speaking, sleep quality is closely related to personal sleep habits, but it is also inseparable from one's basic health. The article does not introduce whether the subjects have basic diseases or basic health conditions. Please supplement.
Response: The Reviewer notes a very good point. We added a Table with the questionnaire that was applied to the users before performing the experiments to detect primary diseases or basic health conditions. We have chosen a sample of 50 healthy people, non-smokers who do not have heart or lung conditions to avoid bias in the experiment. People who have answered "yes" to any of the questions in Table 3 have been discarded from the sample.
“shows the results of the qualitative approach which describes the variables used for the research with 32 samples. These variables are time of sleep, exposure to light and sleep position. The answers for each of the variables were analyzed by comparing whether the participants slept complete cycles or not, whether they had exposure to light or not and whether they slept on a side position, on a back or stomach position. We present the numerical approach of these results to illustrate them. With these results obtained from the 32 samples, we will develop an algorithm to test later on this study.”
Comment 3: Examples of data sources and sleep improvement applications shown in FIGS. 14 and 16. It has no academic value. I suggest it be removed.
Response: The reviewer makes an excellent point. We have improved the scientific content by removing figure 14. Also, if the reviewer agreed, we would leave figure 16 as these images show relevant information from real sleep applications. These data are helpful for the study thanks to the accurate information taken from real sensors already sold in different devices and reported by our experimental subjects. By comparing these results with the results we obtained during the study, we can identify how the person's sleep data improves in the presence of the algorithm. This is as true to our results. Figure 16 has been translated into English for ease.
Comment 4: Figure 15 lists the improvement of sleep quality, but the sleep quality described in the article has many factors, and only the qualitative description is given in Section 2. How are the quantitative results calculated here? Please supplement the calculation model and basis.
Response: This Figure, now Figure 18, needs to be better explained, as the Reviewer mentions. Data presented here is taken from the 50 people in the sample who experience the absence and presence of the algorithm in the sensor network in their room. It is essential to mention that external conditions can influence the experiment, such as the person's mood that day, mood swings, momentary changes in the family environment, etc. However, these data were taken quantitatively during the two weeks of experimentation with electronic devices suitable for medical use in homes. So, in the first week, people do not sleep with the sensor network in their room (no sensors). In the second week, people sleep with the sensor network in operation and the proposed algorithm activated in the devices (sensors). This Figure corresponds to the metrics described in Table 4. Here the behavior of the data is shown in a comparative way and its distribution. We observe how the algorithm's operation is consistent with the person's relaxation, and this impacts their way of sleeping. The foremost vital signs show improvements when people sleep with the sensor network in their room (sensors). Measurements are taken with medical devices used at home to measure temperature, heart rate, breathing frequency, and oxygen saturation. We take a measurement every hour while the subject is asleep. These measurements were made during the week when the subjects do not have the sensor network and during the week when they sleep with the sensor network in their room.
Reviewer 3 comments
Comment 1: The quality of the scientific content on the background of sleeping is very shallow.
Response: Thank you very much the Reviewer for their valuable comments and review of our work. Many thanks to the Reviewer for his extensive comments because they have helped us to improve the manuscript significantly. We have improved the depth of the sleep problem from the technological developments currently available for use at home. We have organized the "Related Work" Section to compare recent work and devices with similar applications. In addition, we have supplemented with a table the primary health conditions of the subjects of our experiment in order not to alter the measurements with external health factors of the people. Also, we have more clearly explained the representative tables and figures on quantitative data that impact sleep to compare the results of people when they sleep without the sensor network and with the sensor network working in their room.
Comment 2: The presentation of the methods used is not enough for a scientific article. There is an image of the devices used to create the wireless network and the configuration of the central unit is presented in unnecessary detail. However, there is no information about the type of sensors, their detection accuracy, etc. This fundamentally calls into questioning the usability of the entire measurement.
Response: The Reviewer is correct. We have added network configuration and deployment checks.
The sensor network in the room system consists of a concentrator or coordinator node, the device connected to the computer via a USB connection. It receives and manages all the information received or transmitted from the network. In addition, it consists of six (6) router/sensor nodes. These devices have eight (8) sensors connected to their communication ports, such as temperature, pressure, humidity, infrared presence (motion), light, sound, gyroscope, and air quality, and they are distributed throughout the room. The parameters are sent via radio frequency to the concentrator or coordinator node in the network.
Table 2 complements the types of sensors in the network. Here we describe the main features and specifications of the sensors to be put into operation in the subjects' room. These sensors are connected to a router node. These router nodes carry the information to the hub node to process the information centrally.
Comment 3: Among the questions "what position did you sleep in?" It was not established scientifically how relevant it is. Furthermore, one usually does not remember it, and it may happen in many different poses.
Response: The Reviewer notes a very good point. Determining in which position a person sleeps in is difficult to know since it may have many different poses. In addition to the importance of sleeping in a certain position due to its benefits, a person may be comfortable with sleeping to a side position due to the benefits of different positions. The first round of questions made were focused on knowing people’s habits, indicating that the position in which they answered was the main position in which they went to sleep. Later in the study, we tested with sensors to get better results, and we got that in less stressful situations, people sleep better. That being said, sleeping in many different poses results in stressful situations. We appreciate the comment because we know it may be confusing when thinking about our poses while sleeping.
Comment 4: The inscriptions "before/after experiments" are limited and unexplained under the graphs (then where is the data from?).
Response: The Reviewer notes a very good point. We analyzed the results of the study and identified the relevant comments of the Reviewer. In result, we improved the study by explaining how we presented the results of the figures showing information of “before/after experiments”. A whole explanation of this section was added to the study in the section before any figure was presented. We appreciate the comment of the reviewer since it is important to explain how we made and analyze the information presented.
“The results of this study show various figures that help explain how people sleep regularly. First of all, we have figures "before experiment". These figures indicates people's actual habits. This helped to obtain base information to move forward into the study. Then we have "during experiment good/bad habits". We obtained this data from the questions made in a control situation to know how people was responding to the experiment. This experiment was divided in two weeks: the first week people adopted bad habits of sleep while the second week people adopted good habits of sleep. Finally, there are figures called "after experiment n week". These figures show the data obtained from a final round of questions made to the samples to know how they generally felt during the experiment. This final data helped us to make a comparison between the base information obtained at the beginning, the data during the experiment and the data after all the questions.”
Comment 5: The mobile phone screen photos, from which data should be read, are of poor quality and do not have English subtitles.
Response: The Reviewer notes a very good point. The mobile phone screen photos do have Spanish labels and we understand the issue there. If the reviewer agrees we may use these photos because we retrieved them due to the relevant information presented in them. These are real photos from real applications of samples of the study. We complement our results of the study with the information from the photos. Figure 17 has been translated into English for ease.
Comment 6: In Table 1, the System type says "Invasive". With a sleep study, it is not described what is invasive, and what is not, but it seems like an exaggeration.
Response: The Reviewer notes a very good point. The reviewer is right for the comment saying that we did not describe what is invasive. As a result, we explained the definition of “Invasive” and “Not invasive” at the beginning of the methodology. In this statement we defined invasive as these devices that people should use or wear most of the time. While noninvasive devices are all these wearables that people must not wear or use because they are placed in their bedroom. We took as reference the text from the public institute of Chile, who states and classifieds the devices in the medical sector. We appreciate the comment of the reviewer because thanks to the observation, we could notice this improvement and we could explain what invasive is.
“Through the study, we mention the use of invasive devices, which we define as devices that are not in direct contact with the person involved. In the medical sector we may use invasive or non-invasive devices that interact directly or indirectly, respectively, with the patient. Since our work uses different system types to determine how our results are obtained. Furthermore, invasive devices should be used by the patient most of the time to obtain these data. In our study, we use mostly non-invasive devices as these are placed around their bedrooms.”
Comment 7: The results include a 9% increase in sleep quality for men and 15% for women. This could easily be a result of measuring technique inaccuracy. Such details of the experiment are not disclosed.
Response: We understand the Reviewer's concern, and he/she is correct that explanations of the accuracy of the experiments were lacking. We have already clarified the sensor system with tables and device configurations. This different result between men and women is interesting because, possibly, women are more strict in following the algorithm's indications at the end of the day. This leads us to think that the slope of sleep rhythm improvement in women may be caused by the implementation of the device measures. For example, if the person has several stops during the night (detected by the motion sensor), the algorithm routes the recommendations towards lower fluid intake.
Another example is based on the fact that if the air quality and temperature sensors show unsuitable conditions for rest, the algorithm's recommendation may be to close some windows at night. This also happens with the abrupt change of levels in the noise sensor. We have clarified these paradigms in the data analysis.
Comment 8: It is hard to understand the results of the measurements in Table 2 with the sensor and without the sensor network. So how did the measurement go? In the meanwhile, the differences are so small that they can simply be measurement errors.
Response: Thank you very much to the Reviewer. We have complemented the explanation by linking Table 5 (previously it was Table 2) with Figure 18 (previously it was Figure 15).
Data presented in Figure 18 is taken from the 50 people in the sample who experience the absence and presence of the algorithm in the sensor network in their room. It is essential to mention that external conditions can influence the experiment, such as the person's mood that day, mood swings, momentary changes in the family environment, etc. However, these data were taken quantitatively during the two weeks of experimentation with electronic devices suitable for medical use in homes. So, in the first week, people do not sleep with the sensor network in their room (no sensors). In the second week, people sleep with the sensor network in operation and the proposed algorithm activated in the devices (sensors). This Figure corresponds to the metrics described in Table 4. Here the behavior of the data is shown in a comparative way and its distribution. We observe how the algorithm's operation is consistent with the person's relaxation, and this impacts their way of sleeping. The foremost vital signs show improvements when people sleep with the sensor network in their room (sensors). Measurements are taken with medical devices used at home to measure temperature, heart rate, breathing frequency, and oxygen saturation. We take a measurement every hour while the subject is asleep. These measurements were made during the week when the subjects do not have the sensor network and during the week when they sleep with the sensor network in their room.
Just as some measurements could have minimal differences, we wanted to make Figure 18. We made this plot to observe better data behavior in the distribution of where most of them were located (the 50% of the box in a box plot and whiskers).
Comment 9: The scale and ranges of the adjacent figures in the data stability chapter are different and subject to misunderstanding.
Response: The Reviewer is right. We appreciate the reviewer pointing out that the figures had different scales and ranged in the data. In consequence, we modified the scale of the figures so that comparison is fair between figures. We avoided modifying and altering the data from these figures so that its consistency remains valid. Furthermore, we complemented the description of the figures so that it is more understandable with the data. We would like to recognize that the design of the figures changed since the scale of each of them changes, however, we would like to clarify that no data was changed in this figure improvement.
“We chose these three persons randomly from the total sample of 50 to evidence the data behavior in the sampling period stability.”
Thank you very much.
Sincerely,
Carolina Del-Valle-Soto
Corresponding author
Universidad Panamericana. Facultad de Ingeniería. Álvaro del Portillo 49, Zapopan, Jalisco, 45010, México.
Phone: +52 (33) 13682200 | Ext. 4866
Email: [email protected]
Author Response File: Author Response.pdf
Round 2
Reviewer 2 Report
I am glad to proceed this manuscript to publication stage.
Author Response
Thank you very much.
Reviewer 3 Report
The reviewer acknowledges the positive improvements of the manuscript. However, numerous issues remain, and some newly added parts require consideration as well. E.g., this sentence is new and requires a double check: "Through the study, we mention the use of invasive devices, which we define as devices that are not in direct contact with the person involved." It is likely that the authors wanted to write non-invasive.
Gyroscope can be found in the list of sensors. If there is no direct contact between the sensors and the subjects, what does the gyroscope measure?
The router configuration is still too detailed and not relevant, authors shall delete it. They should rather write about network speed, protocols, latency. if they want something from the router at all cost.
Minor issues:
The authors changed the Spanish mobile screenshots to English, but it is still not well readable, only zoomed to 200% on the 27" monitor. Please improve!
"Table 18" is referenced, but there is only "Table 6", it is likely that they wanted to write Figure.
At first glance, the inscriptions on the horizontal axis are not clear in figures 22, 23, 24. (Isn't the "ID person" on the other figures strange? Should it be written that way?)
No space is left between the figure captions and the paragraph following them,
Author Response
Dear
Editor
Future Internet
We are submitting the paper:
“Analysis and correlation between a non-invasive sensor network system in the room and the improvement of sleep quality”
Authored by: Eduardo Morales-Vizcarra, Carolina Del-Valle-Soto*, Paolo Visconti, and Fabiola Cortes-Chavez.
We would like to thank the reviewers and editors for their detailed analysis of the manuscript; the comments are very valuable to us. In the revised version of the paper, we have incorporated the all changes recommended by the reviewers.
Comments to all observations and suggestions including point-by-point responses are addressed in the following text.
Reviewer 3 comments
Comment 1: The reviewer acknowledges the positive improvements of the manuscript. However, numerous issues remain, and some newly added parts require consideration as well. E.g., this sentence is new and requires a double check: "Through the study, we mention the use of invasive devices, which we define as devices that are not in direct contact with the person involved." It is likely that the authors wanted to write non-invasive.
Response: The Reviewer is correct, and we have corrected the word to "non-invasive". Likewise, we have carefully reviewed the entire manuscript to find these errors or inaccuracies.
Comment 2: Gyroscope can be found in the list of sensors. If there is no direct contact between the sensors and the subjects, what does the gyroscope measure?
Response: Many thanks to the Reviewer. We extended the explanation about using the gyroscope as a sensor for clarity. Motion sensors are useful for monitoring device movements, such as tilt, vibration, rotation, or sway. During a sensor event, the accelerometer displays acceleration force data for all three coordinate axes, and the gyroscope displays rotational speed data for those same axes. The gyroscope is located at the room's doors to count the number of times these doors turn, and the subject enters the bathroom or leaves his room at night. This may be an indicator of poor sleep in the person.
Comment 3: The router configuration is still too detailed and not relevant, authors shall delete it. They should rather write about network speed, protocols, latency. if they want something from the router at all cost.
Response: Thanks to the Reviewer for bringing these comments to our attention. We have removed the overly detailed router specs. We think that the detail of the system and the topology presented is sufficient since it is a WiFi network widely known for its characteristics, speeds, and delays.
Minor issues:
Comment 4: The authors changed the Spanish mobile screenshots to English, but it is still not well readable, only zoomed to 200% on the 27" monitor. Please improve!
Response: Many thanks to the Reviewer. We have separated the Figures and increased the resolution so they can be seen more clearly.
Comment 5: "Table 18" is referenced, but there is only "Table 6", it is likely that they wanted to write Figure.
Response: Indeed, the Reviewer is correct and we have changed the word “Table” to “Figure”.
Comment 6: At first glance, the inscriptions on the horizontal axis are not clear in figures 22, 23, 24. (Isn't the "ID person" on the other figures strange? Should it be written that way?)
Response: Thank you for your comment, and we understand the confusion. With these four figures, we want to show that we chose three people randomly from the 50 people in the sample. Therefore, on the "x" axis, we put ID person because it is a random ID of a person between 1 and 50.
Comment 7: No space is left between the figure captions and the paragraph following them,
Response: Thanks to the Reviewer for his detailed comments. The MDPI template does not let us modify this, but we will keep it in mind to make it look good when reviewing with the style editor.
Thank you very much.
Sincerely,
Carolina Del-Valle-Soto
Corresponding author
Universidad Panamericana. Facultad de Ingeniería. Álvaro del Portillo 49, Zapopan, Jalisco, 45010, México.
Phone: +52 (33) 13682200 | Ext. 4866
Email: [email protected]
Author Response File: Author Response.pdf
Round 3
Reviewer 3 Report
The authors managed to improve the article, nevertheless, its scientific depth and rigorousness are still limited. The authors should do a better job in positioning their research relative to the state of the art. There are numerous other projects ongoing: https://scholar.google.hu/scholar?hl=en&as_sdt=0%2C21&q=sleep+monitoring&btnG=
Author Response
Many thanks to the Reviewer for his timely comments. We have substantially improved the study of related works reported comparatively and analyzed the metrics studied to make fair comparisons with our proposal. In addition, we want to mention that the fundamental idea of our work is to present a novel and low-energy consumption algorithm for a network of sensors installed in a person's room that monitors sleep without being in direct contact.
